mirror of
https://github.com/labring/FastGPT.git
synced 2025-08-06 23:56:35 +00:00
Change embedding (#1463)
* rebuild embedding queue * dataset menu * feat: rebuild data api * feat: ui change embedding model * dataset ui * feat: rebuild index ui * rename collection
This commit is contained in:
@@ -1,33 +1,22 @@
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import React, { useCallback, useMemo } from 'react';
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import { useRouter } from 'next/router';
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import { Box, Flex, IconButton, useTheme, Progress } from '@chakra-ui/react';
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import { Box } from '@chakra-ui/react';
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import { useToast } from '@fastgpt/web/hooks/useToast';
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import { useQuery } from '@tanstack/react-query';
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import { getErrText } from '@fastgpt/global/common/error/utils';
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import { useSystemStore } from '@/web/common/system/useSystemStore';
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import Tabs from '@/components/Tabs';
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import dynamic from 'next/dynamic';
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import MyIcon from '@fastgpt/web/components/common/Icon';
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import SideTabs from '@/components/SideTabs';
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import PageContainer from '@/components/PageContainer';
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import Avatar from '@/components/Avatar';
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import { serviceSideProps } from '@/web/common/utils/i18n';
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import { useTranslation } from 'next-i18next';
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import { getTrainingQueueLen } from '@/web/core/dataset/api';
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import MyTooltip from '@/components/MyTooltip';
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import CollectionCard from './components/CollectionCard';
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import { useDatasetStore } from '@/web/core/dataset/store/dataset';
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import { useUserStore } from '@/web/support/user/useUserStore';
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import {
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DatasetStatusEnum,
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DatasetTypeEnum,
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DatasetTypeMap
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} from '@fastgpt/global/core/dataset/constants';
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import { useConfirm } from '@fastgpt/web/hooks/useConfirm';
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import { useRequest } from '@fastgpt/web/hooks/useRequest';
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import DatasetTypeTag from '@/components/core/dataset/DatasetTypeTag';
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import Head from 'next/head';
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import Slider from './components/Slider';
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import MyBox from '@fastgpt/web/components/common/MyBox';
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import { DatasetPageContextProvider } from '@/web/core/dataset/context/datasetPageContext';
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const DataCard = dynamic(() => import('./components/DataCard'));
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const Test = dynamic(() => import('./components/Test'));
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@@ -42,48 +31,16 @@ export enum TabEnum {
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import = 'import'
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}
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const Detail = ({ datasetId, currentTab }: { datasetId: string; currentTab: `${TabEnum}` }) => {
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const theme = useTheme();
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const Detail = ({ datasetId, currentTab }: { datasetId: string; currentTab: TabEnum }) => {
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const { t } = useTranslation();
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const { toast } = useToast();
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const router = useRouter();
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const { isPc } = useSystemStore();
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const { datasetDetail, loadDatasetDetail, startWebsiteSync } = useDatasetStore();
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const { userInfo } = useUserStore();
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const tabList = [
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{
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label: t('core.dataset.Collection'),
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id: TabEnum.collectionCard,
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icon: 'common/overviewLight'
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},
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{ label: t('core.dataset.test.Search Test'), id: TabEnum.test, icon: 'kbTest' },
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...(userInfo?.team.canWrite && datasetDetail.isOwner
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? [{ label: t('common.Config'), id: TabEnum.info, icon: 'common/settingLight' }]
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: [])
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];
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const { datasetDetail, loadDatasetDetail } = useDatasetStore();
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const { ConfirmModal: ConfirmSyncModal, openConfirm: openConfirmSync } = useConfirm({
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type: 'common'
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});
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const { mutate: onUpdateDatasetWebsiteConfig, isLoading: isUpdating } = useRequest({
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mutationFn: () => startWebsiteSync(),
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errorToast: t('common.Update Failed')
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});
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const setCurrentTab = useCallback(
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(tab: `${TabEnum}`) => {
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router.replace({
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query: {
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datasetId,
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currentTab: tab
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}
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});
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},
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[datasetId, router]
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);
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useQuery([datasetId], () => loadDatasetDetail(datasetId), {
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onError(err: any) {
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router.replace(`/dataset/list`);
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@@ -94,197 +51,33 @@ const Detail = ({ datasetId, currentTab }: { datasetId: string; currentTab: `${T
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}
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});
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const { data: { vectorTrainingCount = 0, agentTrainingCount = 0 } = {} } = useQuery(
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['getTrainingQueueLen'],
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() =>
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getTrainingQueueLen({
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vectorModel: datasetDetail.vectorModel.model,
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agentModel: datasetDetail.agentModel.model
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}),
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{
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refetchInterval: 10000
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}
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);
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const { vectorTrainingMap, agentTrainingMap } = useMemo(() => {
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const vectorTrainingMap = (() => {
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if (vectorTrainingCount < 1000)
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return {
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colorSchema: 'green',
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tip: t('core.dataset.training.Leisure')
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};
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if (vectorTrainingCount < 10000)
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return {
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colorSchema: 'yellow',
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tip: t('core.dataset.training.Waiting')
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};
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return {
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colorSchema: 'red',
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tip: t('core.dataset.training.Full')
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};
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})();
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const agentTrainingMap = (() => {
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if (agentTrainingCount < 100)
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return {
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colorSchema: 'green',
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tip: t('core.dataset.training.Leisure')
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};
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if (agentTrainingCount < 1000)
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return {
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colorSchema: 'yellow',
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tip: t('core.dataset.training.Waiting')
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};
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return {
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colorSchema: 'red',
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tip: t('core.dataset.training.Full')
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};
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})();
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return {
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vectorTrainingMap,
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agentTrainingMap
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};
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}, [agentTrainingCount, t, vectorTrainingCount]);
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return (
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<>
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<Head>
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<title>{datasetDetail?.name}</title>
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</Head>
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<PageContainer>
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<MyBox
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isLoading={isUpdating}
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display={'flex'}
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flexDirection={['column', 'row']}
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h={'100%'}
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pt={[4, 0]}
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>
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{isPc ? (
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<Flex
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flexDirection={'column'}
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py={4}
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h={'100%'}
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flex={'0 0 200px'}
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borderRight={theme.borders.base}
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>
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<Box px={4} borderBottom={'1px'} borderColor={'myGray.200'} pb={4} mb={4}>
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<Flex mb={4} alignItems={'center'}>
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<Avatar src={datasetDetail.avatar} w={'34px'} borderRadius={'md'} />
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<Box ml={2}>
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<Box fontWeight={'bold'}>{datasetDetail.name}</Box>
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</Box>
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</Flex>
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{DatasetTypeMap[datasetDetail.type] && (
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<Flex alignItems={'center'} pl={2} justifyContent={'space-between'}>
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<DatasetTypeTag type={datasetDetail.type} />
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{datasetDetail.type === DatasetTypeEnum.websiteDataset &&
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datasetDetail.status === DatasetStatusEnum.active && (
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<MyTooltip label={t('core.dataset.website.Start Sync')}>
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<MyIcon
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mt={1}
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name={'common/refreshLight'}
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w={'12px'}
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color={'myGray.500'}
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cursor={'pointer'}
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onClick={() =>
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openConfirmSync(
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onUpdateDatasetWebsiteConfig,
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undefined,
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t('core.dataset.website.Confirm Create Tips')
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)()
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}
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/>
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</MyTooltip>
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)}
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</Flex>
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)}
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</Box>
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<SideTabs
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px={4}
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flex={1}
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mx={'auto'}
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w={'100%'}
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list={tabList}
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activeId={currentTab}
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onChange={(e: any) => {
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setCurrentTab(e);
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}}
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/>
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<Box px={4}>
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<Box mb={3}>
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<Box fontSize={'sm'}>
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{t('core.dataset.training.Agent queue')}({agentTrainingMap.tip})
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</Box>
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<Progress
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value={100}
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size={'xs'}
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colorScheme={agentTrainingMap.colorSchema}
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borderRadius={'10px'}
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isAnimated
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hasStripe
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/>
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</Box>
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<Box mb={3}>
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<Box fontSize={'sm'}>
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{t('core.dataset.training.Vector queue')}({vectorTrainingMap.tip})
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</Box>
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<Progress
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value={100}
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size={'xs'}
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colorScheme={vectorTrainingMap.colorSchema}
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borderRadius={'10px'}
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isAnimated
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hasStripe
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/>
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</Box>
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</Box>
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<DatasetPageContextProvider
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value={{
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datasetId
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}}
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>
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<PageContainer>
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<MyBox display={'flex'} flexDirection={['column', 'row']} h={'100%'} pt={[4, 0]}>
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<Slider currentTab={currentTab} />
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<Flex
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alignItems={'center'}
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cursor={'pointer'}
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py={2}
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px={3}
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borderRadius={'md'}
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_hover={{ bg: 'myGray.100' }}
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onClick={() => router.replace('/dataset/list')}
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>
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<IconButton
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mr={3}
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icon={<MyIcon name={'common/backFill'} w={'18px'} color={'primary.500'} />}
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bg={'white'}
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boxShadow={'1px 1px 9px rgba(0,0,0,0.15)'}
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size={'smSquare'}
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borderRadius={'50%'}
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aria-label={''}
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/>
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{t('core.dataset.All Dataset')}
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</Flex>
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</Flex>
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) : (
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<Box mb={3}>
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<Tabs
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m={'auto'}
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w={'260px'}
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size={isPc ? 'md' : 'sm'}
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list={tabList.map((item) => ({
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id: item.id,
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label: item.label
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}))}
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activeId={currentTab}
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onChange={(e: any) => setCurrentTab(e)}
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/>
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</Box>
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)}
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{!!datasetDetail._id && (
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<Box flex={'1 0 0'} pb={0}>
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{currentTab === TabEnum.collectionCard && <CollectionCard />}
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{currentTab === TabEnum.dataCard && <DataCard />}
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{currentTab === TabEnum.test && <Test datasetId={datasetId} />}
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{currentTab === TabEnum.info && <Info datasetId={datasetId} />}
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{currentTab === TabEnum.import && <Import />}
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</Box>
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)}
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</MyBox>
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</PageContainer>
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</DatasetPageContextProvider>
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{!!datasetDetail._id && (
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<Box flex={'1 0 0'} pb={0}>
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{currentTab === TabEnum.collectionCard && <CollectionCard />}
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{currentTab === TabEnum.dataCard && <DataCard />}
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{currentTab === TabEnum.test && <Test datasetId={datasetId} />}
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{currentTab === TabEnum.info && <Info datasetId={datasetId} />}
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{currentTab === TabEnum.import && <Import />}
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</Box>
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)}
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</MyBox>
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</PageContainer>
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<ConfirmSyncModal />
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</>
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);
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@@ -295,7 +88,7 @@ export async function getServerSideProps(context: any) {
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const datasetId = context?.query?.datasetId;
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return {
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props: { currentTab, datasetId, ...(await serviceSideProps(context, ['file'])) }
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props: { currentTab, datasetId, ...(await serviceSideProps(context, ['dataset', 'file'])) }
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};
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}
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